Raghavendra Ashrit

1.7k total citations
63 papers, 1.2k citations indexed

About

Raghavendra Ashrit is a scholar working on Atmospheric Science, Global and Planetary Change and Oceanography. According to data from OpenAlex, Raghavendra Ashrit has authored 63 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 57 papers in Atmospheric Science, 52 papers in Global and Planetary Change and 4 papers in Oceanography. Recurrent topics in Raghavendra Ashrit's work include Meteorological Phenomena and Simulations (50 papers), Climate variability and models (46 papers) and Tropical and Extratropical Cyclones Research (22 papers). Raghavendra Ashrit is often cited by papers focused on Meteorological Phenomena and Simulations (50 papers), Climate variability and models (46 papers) and Tropical and Extratropical Cyclones Research (22 papers). Raghavendra Ashrit collaborates with scholars based in India, United Kingdom and Australia. Raghavendra Ashrit's co-authors include Kireet Kumar, K. Rupa Kumar, E. N. Rajagopal, James Hansen, K. Rupa Kumar, N. R. Deshpande, Someshwar Das, Mitchell W. Moncrieff, Gopal Iyengar and Anumeha Dube and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Geophysical Research Atmospheres and Geophysical Research Letters.

In The Last Decade

Raghavendra Ashrit

55 papers receiving 1.2k citations

Peers

Raghavendra Ashrit

GPC

EEBS

OCEAN

G. T. Diro Canada

C. Boroneanţ Spain

Armelle Reca Remedio Germany

K. Rupa Kumar India

B. N. Goswami India

Lydia Stefanova United States

Laura Mariotti Italy

Akhil Srivastava India

Margot Bador France

G. T. Diro Canada

Raghavendra Ashrit

1.2k ×1.3

GPC

911 ×1.1

190 ×1.0

EEBS

117 ×1.2

OCEAN

110 ×1.2

Citations per year, relative to Raghavendra Ashrit Raghavendra Ashrit (= 1×) peers G. T. Diro

Countries citing papers authored by Raghavendra Ashrit

Since Specialization

Citations

This map shows the geographic impact of Raghavendra Ashrit's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Raghavendra Ashrit with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raghavendra Ashrit more than expected).

Fields of papers citing papers by Raghavendra Ashrit

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Raghavendra Ashrit. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Raghavendra Ashrit. The network helps show where Raghavendra Ashrit may publish in the future.

Co-authorship network of co-authors of Raghavendra Ashrit

This figure shows the co-authorship network connecting the top 25 collaborators of Raghavendra Ashrit. A scholar is included among the top collaborators of Raghavendra Ashrit based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Raghavendra Ashrit. Raghavendra Ashrit is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Ashrit, Raghavendra, et al.. (2025). Wind power forecasting over India: value-addition to a coupled model seasonal forecasts. Clean Energy. 9(2). 37–51. 2 indexed citations

Singh, H. N., Anumeha Dube, Raghavendra Ashrit, Prashant K. Srivastava, & V. S. Prasad. (2025). Object-based forecasting of heat waves over India: A novel approach. Journal of Earth System Science. 134(3).

Ashrit, Raghavendra, et al.. (2025). Wind speed and power forecasting: Evaluating NCUM-G model performance. Journal of Earth System Science. 134(1). 1 indexed citations

Ashrit, Raghavendra, et al.. (2025). Prediction of lightning events over Bangladesh: A machine learning perspective. Journal of Atmospheric and Solar-Terrestrial Physics. 268. 106448–106448.

Pandey, Lokesh Kumar, et al.. (2025). Dynamical Mechanisms of Rapid Intensification and Multiple Recurvature of Pre-Monsoonal Tropical Cyclone Mocha over the Bay of Bengal. SHILAP Revista de lepidopterología. 4(2). 9–9.

Widmann, Martin, et al.. (2024). A comparison of two statistical postprocessing methods for heavy‐precipitation forecasts over India during the summer monsoon. Quarterly Journal of the Royal Meteorological Society. 150(761). 1865–1883. 3 indexed citations

Kumar, Kondapalli Niranjan, Akhilesh Mishra, Raghavendra Ashrit, et al.. (2024). Unraveling Subseasonal Drought Dynamics in India: Insights from NCMRWF Extended Range Prediction System. Journal of Hydrometeorology. 25(8). 1191–1207. 1 indexed citations

Ashrit, Raghavendra, Kondapalli Niranjan Kumar, Upal Saha, et al.. (2024). Assessment of extreme rainfall events for iFLOWS Mumbai in NCUM regional forecasting system. Natural Hazards. 120(12). 10785–10805. 3 indexed citations

Marsigli, Chiara, Elizabeth E. Ebert, Raghavendra Ashrit, et al.. (2021). Review article: Observations for high-impact weather and their use in verification. Natural hazards and earth system sciences. 21(4). 1297–1312. 12 indexed citations

10.

Arulalan, T., et al.. (2020). Extended-range prediction of heatwave events over North India: role of atmospheric blocking over North Atlantic. 1 indexed citations

11.

Marsigli, Chiara, Elizabeth E. Ebert, Raghavendra Ashrit, et al.. (2020). Observations for high-impact weather and their use in verification. 3 indexed citations

12.

Sharma, Kuldeep, et al.. (2019). Evaluation of Unified Model Rainfall Forecasts over the Western Ghats and North East states of India. 3 indexed citations

13.

Singh, H. N., et al.. (2017). Verification of pre-monsoon temperature forecasts over India during 2016 with a focus on heatwave prediction. Natural hazards and earth system sciences. 17(9). 1469–1485. 23 indexed citations

14.

Iyengar, Gopal, Raghavendra Ashrit, Kuldeep Sharma, et al.. (2014). Improved Prediction of Cyclone Phailin (9-12 October 2013) with 4DVAR Assimilation. Current Science. 107(6). 952–954. 2 indexed citations

15.

Dube, Anumeha, Raghavendra Ashrit, Kuldeep Sharma, et al.. (2014). Forecasting the heavy rainfall during Himalayan flooding—June 2013. Weather and Climate Extremes. 4. 22–34. 67 indexed citations

16.

Das, Someshwar, Raghavendra Ashrit, Gopal Iyengar, et al.. (2008). Skills of different mesoscale models over Indian region during monsoon season: Forecast errors. Journal of Earth System Science. 117(5). 603–620. 48 indexed citations

17.

Bohra, A. K., Swati Basu, E. N. Rajagopal, et al.. (2006). Heavy rainfall episode over Mumbai on 26 July 2005: Assessment of NWP guidance. Current Science. 90(9). 1188–1194. 56 indexed citations

18.

Ashrit, Raghavendra, Akio Kitoh, & Seiji Yukimoto. (2005). Transient Response of ENSO-Monsoon Teleconnection in MRI-CGCM2.2 Climate Change Simulations. Journal of the Meteorological Society of Japan Ser II. 83(3). 273–291. 31 indexed citations

19.

Kumar, Kireet, et al.. (2004). Climate impacts on Indian agriculture. International Journal of Climatology. 24(11). 1375–1393. 328 indexed citations

20.

Ashrit, Raghavendra, Hervé Douville, & K. Rupa Kumar. (2003). Response of the Indian Monsoon and ENSO-Monsoon Teleconnection to Enhanced Greenhouse Effect in the CNRM Coupled Model. Journal of the Meteorological Society of Japan Ser II. 81(4). 779–803. 61 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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